added a few eda plotting functions #373
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eda plotting functions
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thanks @Ariel77 for this. could you please add an example notebook so that it is easier to review and understand what each plotting utility is doing? in orbit, we have many example data sets. if you want, you could use |
Add weekly_trend_decomposition function to plot weekly trend, seasonality and residual.
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| df_dt = deepcopy(df) | ||
| df_dt.index = pd.to_datetime(df_dt[date_col]) | ||
| res_weely = seasonal_decompose(df_dt[[var]], period=7, model='multiplicative') |
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I am trying to generate some EDA plots so looking at this code to borrow some ideas. A quick question, where do we get this seasonal_decompose(). Thanks!
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@Ariel77 @xiaoyangzhou thanks for the new commits. still, could we have one notebook to demo these functions? it can help review the code. |
Sure. @Ariel77 I can work on the demo notebook. Let me know if you already create one. |
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I already created one, but with internal data.
I can quickly swap to the iclaim data.
Will push end of this week.
On Wed, Mar 10, 2021 at 5:46 PM xiaoyangzhou ***@***.***> wrote:
@Ariel77 <https://github.com/Ariel77> @xiaoyangzhou
<https://github.com/xiaoyangzhou> thanks for the new commits. still,
could we have one notebook to demo these functions? it can help review the
code.
Sure. @Ariel77 <https://github.com/Ariel77> I can work on the demo
notebook. Let me know if you already create one.
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1. eda_plot.py: using seasonal_decompose function from statsmodels.tsa.seasonal. 2. eda_function_demo.ipynb: used iclaims_example.csv to generate eda plots.
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addressed in a separate PR |
eda 5 plotting functions
Description
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Fixes # (issue)
Type of change
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How Has This Been Tested?
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manual tests